Model comparison
GPT-4o vs Muse Spark 1.2
Muse Spark 1.2 is the stronger model overall, scoring 50.3 to 28.6 on the Noometry Index.
Last verified . 22 shared benchmarks.
MetaSummary
- They share 22 benchmarks with published results for both. GPT-4o scores higher in 0 categories and Muse Spark 1.2 in 10 categories; 10 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where Muse Spark 1.2 leads 51.3 to 9.4.
- The biggest single-benchmark swing is SimpleBench: 17.8% for GPT-4o and 74.5% for Muse Spark 1.2.
- Muse Spark 1.2 is cheaper at $1.25 / $4.25 per million input/output tokens, against $2.50 / $10 for GPT-4o.
- Muse Spark 1.2 accepts more context: 1.05M tokens versus 128K.
Side by side
| GPT-4o | Muse Spark 1.2 | |
|---|---|---|
| Provider | OpenAI | Meta |
| Noometry Index | 28.6 | 50.3 |
| Released | 2024-05-13 | 2026-08-05 |
| Weights | Proprietary | Proprietary |
| Context window | 128K | 1.05M |
| Max output | 16K | 131K |
| Input $ / M tokens | $2.50 | $1.25 |
| Output $ / M tokens | $10 | $4.25 |
| Results tracked | 72 | 31 |
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Category by category
Coding Muse Spark 1.2 leads
GPT-4o: 24.8 (#328), Muse Spark 1.2: 49.2 (#51)
| Benchmark | GPT-4o | Muse Spark 1.2 |
|---|---|---|
| WeirdML | 25.1% | 60.3% |
| LMArena Coding | 1297 | 1495 |
| SWE-bench Verified | 31% | — |
| DeepSWE | — | 54.9% |
| SWE-bench Verified (bash only) | 21.6% | — |
| Aider Polyglot | 45.3% | — |
| LMArena WebDev | — | 1533 |
| FrontierSWE | — | 12% |
| SciCode | — | 56.4% |
| GSO | 0% | — |
| BigCodeBench Instruct | 51.1% | — |
| LiveBench Coding | 51.4% | — |
| BigCodeBench Complete | 61.1% | — |
| CadEval | 26% | — |
| HumanEval+ | 87.2% | — |
| MBPP+ | 72.2% | — |
Agentic & Tool Use Muse Spark 1.2 leads
GPT-4o: 21.0 (#141), Muse Spark 1.2: 29.4 (#87)
| Benchmark | GPT-4o | Muse Spark 1.2 |
|---|---|---|
| APEX-Agents | — | 36.4% |
| GDPval | 9.9% | — |
| TheAgentCompany | 8.6% | — |
| Cybench | 12.5% | — |
| BALROG | 32.3% | — |
| GDP.pdf | — | 16% |
| LMArena Search | 1006 | — |
| METR Time Horizons | 40.8% | — |
Reasoning Muse Spark 1.2 leads
GPT-4o: 9.4 (#343), Muse Spark 1.2: 51.3 (#34)
| Benchmark | GPT-4o | Muse Spark 1.2 |
|---|---|---|
| SimpleBench | 17.8% | 74.5% |
| CritPt | 0% | 17.7% |
| LMArena Hard Prompts | 1281 | 1486 |
| DTBench | 64.5% | 94.7% |
| LMCA | 16.6% | 48.4% |
| Epoch Capabilities Index | 128.97 | 154.87 |
| ARC-AGI-2 | 0% | — |
| NYT Connections (extended) | — | 79.2% |
| ARC-AGI-1 | 4.5% | — |
| Chess Puzzles | 13% | — |
| EnigmaEval | 0.8% | — |
| LiveBench Reasoning | 55.8% | — |
| LiveBench Data Analysis | 60.9% | — |
| ForecastBench | 57.7 | — |
| LiveBench | 55.3% | — |
Math Muse Spark 1.2 leads
GPT-4o: 10.6 (#312), Muse Spark 1.2: 46.4 (#70)
| Benchmark | GPT-4o | Muse Spark 1.2 |
|---|---|---|
| LMArena Math | 1285 | 1471 |
| FrontierMath (Tiers 1-3) | 0.4% | — |
| OTIS Mock AIME 2024-2025 | 6.4% | — |
| ProofBench | — | 43% |
| Omni-MATH | 29.3% | — |
| LiveBench Math | 49.5% | — |
| MATH Level 5 | 53.3% | — |
| FrontierMath (Feb 2025 set) | 0.3% | — |
Knowledge Muse Spark 1.2 leads
GPT-4o: 28.8 (#242), Muse Spark 1.2: 54.1 (#53)
| Benchmark | GPT-4o | Muse Spark 1.2 |
|---|---|---|
| SimpleQA Verified | 26% | 60.3% |
| LMArena Expert | 1250 | 1480 |
| GPQA Diamond | 49.2% | — |
| Humanity's Last Exam | 2.7% | — |
| MMLU-Pro | 71.3% | — |
| Confabulations | 15.3% | — |
| Vectara Hallucination Rate | 9.6% | — |
| GPQA (HELM) | 52% | — |
| MMLU | 88.1% | — |
Multimodal Muse Spark 1.2 leads
GPT-4o: 34.5 (#91), Muse Spark 1.2: 43.4 (#25)
| Benchmark | GPT-4o | Muse Spark 1.2 |
|---|---|---|
| LMArena Vision | 1137 | 1305 |
| Video-MME | 71.9% | — |
| GeoBench | 71% | — |
| VPCT | 40% | — |
| ScienceQA | 88.5% | — |
Multilingual Muse Spark 1.2 leads
GPT-4o: 43.2 (#186), Muse Spark 1.2: 57.1 (#11)
| Benchmark | GPT-4o | Muse Spark 1.2 |
|---|---|---|
| LMArena Non-English | 1283 | 1478 |
| LMArena Chinese | 1277 | 1511 |
| LMArena French | 1304 | 1513 |
| LMArena Russian | 1286 | 1487 |
| LMArena Spanish | 1292 | 1498 |
| LMArena German | 1282 | — |
| LMArena Japanese | 1257 | — |
| LMArena Korean | 1234 | — |
Instruction Following Muse Spark 1.2 leads
GPT-4o: 66.6 (#207), Muse Spark 1.2: 76.7 (#36)
| Benchmark | GPT-4o | Muse Spark 1.2 |
|---|---|---|
| LMArena Instruction Following | 1278 | 1461 |
| LiveBench Instruction Following | 68.6% | — |
| IFEval | 81.7% | — |
Long Context Muse Spark 1.2 leads
GPT-4o: 39.4 (#179), Muse Spark 1.2: 45.2 (#48)
| Benchmark | GPT-4o | Muse Spark 1.2 |
|---|---|---|
| LMArena Longer Query | 1289 | 1475 |
| Fiction.LiveBench | 66.7% | — |
Writing & Preference Muse Spark 1.2 leads
GPT-4o: 52.6 (#166), Muse Spark 1.2: 72.3 (#14)
| Benchmark | GPT-4o | Muse Spark 1.2 |
|---|---|---|
| LMArena Text | 1300 | 1482 |
| LMArena Creative Writing | 1292 | 1449 |
| LMArena Multi-Turn | 1302 | 1494 |
| Short-Story Creative Writing | 81.8% | — |
| EQ-Bench Creative Writing | — | 1840 |
| WildBench | 82.8% | — |
| LiveBench Language | 47.6% | — |
Frequently asked questions
Is GPT-4o better than Muse Spark 1.2?
Muse Spark 1.2 is the stronger model overall, scoring 50.3 to 28.6 on the Noometry Index.
Which is cheaper, GPT-4o or Muse Spark 1.2?
Muse Spark 1.2 is cheaper. It lists at $1.25 per million input tokens and $4.25 per million output tokens; GPT-4o lists at $2.50 and $10.
Is GPT-4o or Muse Spark 1.2 better for coding?
Muse Spark 1.2 scores higher on coding benchmarks: 49.2 versus 24.8 in the Noometry coding category.
Which has the bigger context window?
Muse Spark 1.2 does, with 1.05M tokens against 128K.
How many benchmarks do GPT-4o and Muse Spark 1.2 share?
22 benchmarks have published results for both models. GPT-4o has 72 scored results on Noometry and Muse Spark 1.2 has 31.